How to Use the HRBlade MCP in AutoGen

Debate your hiring decisions using AutoGen multi-agent systems connected to your live HRBlade recruitment data.

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Connect HRBlade MCP to AutoGen

Create your Vinkius account to connect HRBlade to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup HRBlade with AutoGen

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Perplexity

Debating HRBlade tasks with AutoGen

Let your agents argue over candidate fit. One agent can call `get_candidate_details` while another reviews the `list_interview_responses` to reach a consensus on whether to proceed. This prevents single-agent bias. You get a system that challenges its own conclusions before it ever sends an invitation.

Multi-agent interview scheduling via AutoGen

Assign an agent to manage the calendar and another to watch for errors. When the scheduling agent calls `create_interview`, the supervisor agent checks the output against existing data. This adds a layer of verification to your workflow. You aren't relying on a single script, but a team of agents that negotiate the best path forward.

Consensus-driven HRBlade actions in AutoGen

Enable agents to negotiate before taking action. If you use `send_interview_invitation`, the agent must first get approval from the team, ensuring every invite aligns with your current hiring goals. This is for when the right decision isn't obvious. The agents deliberate, check the data, and only act once they agree on the next step.

Setup guide

Set up HRBlade MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes HRBlade tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="HRBlade_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent HRBlade data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="HRBlade_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent HRBlade data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by HRBlade. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about HRBlade MCP in AutoGen

Install the MCP extension for AutoGen. Use the server parameters to point your agents at the endpoint, and they will automatically see the available tools.

That is the point. You can configure one agent to prioritize speed and another to prioritize quality, forcing them to debate the best candidate to interview.

Yes, the adapter handles it for you. Your agents see the tools as native functions and can call them as part of their conversation.

You control the permissions. You can set up a human-in-the-loop agent that must approve any `send_interview_invitation` call before it executes.

The server enforces strict access controls. Each agent only receives the specific candidate information it needs to complete its assigned debate task, keeping PII isolated.

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